{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d43a5d47-93a0-4022-91b0-e3299a4ce682",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2a1d2635-43b5-4ed8-933d-dfed6d8199bd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date Time</th>\n",
       "      <th>p (mbar)</th>\n",
       "      <th>T (degC)</th>\n",
       "      <th>Tpot (K)</th>\n",
       "      <th>Tdew (degC)</th>\n",
       "      <th>rh (%)</th>\n",
       "      <th>VPmax (mbar)</th>\n",
       "      <th>VPact (mbar)</th>\n",
       "      <th>VPdef (mbar)</th>\n",
       "      <th>sh (g/kg)</th>\n",
       "      <th>H2OC (mmol/mol)</th>\n",
       "      <th>rho (g/m**3)</th>\n",
       "      <th>wv (m/s)</th>\n",
       "      <th>max. wv (m/s)</th>\n",
       "      <th>wd (deg)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01.01.2009 00:10:00</td>\n",
       "      <td>996.52</td>\n",
       "      <td>-8.02</td>\n",
       "      <td>265.40</td>\n",
       "      <td>-8.90</td>\n",
       "      <td>93.3</td>\n",
       "      <td>3.33</td>\n",
       "      <td>3.11</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.94</td>\n",
       "      <td>3.12</td>\n",
       "      <td>1307.75</td>\n",
       "      <td>1.03</td>\n",
       "      <td>1.75</td>\n",
       "      <td>152.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01.01.2009 00:20:00</td>\n",
       "      <td>996.57</td>\n",
       "      <td>-8.41</td>\n",
       "      <td>265.01</td>\n",
       "      <td>-9.28</td>\n",
       "      <td>93.4</td>\n",
       "      <td>3.23</td>\n",
       "      <td>3.02</td>\n",
       "      <td>0.21</td>\n",
       "      <td>1.89</td>\n",
       "      <td>3.03</td>\n",
       "      <td>1309.80</td>\n",
       "      <td>0.72</td>\n",
       "      <td>1.50</td>\n",
       "      <td>136.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01.01.2009 00:30:00</td>\n",
       "      <td>996.53</td>\n",
       "      <td>-8.51</td>\n",
       "      <td>264.91</td>\n",
       "      <td>-9.31</td>\n",
       "      <td>93.9</td>\n",
       "      <td>3.21</td>\n",
       "      <td>3.01</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.88</td>\n",
       "      <td>3.02</td>\n",
       "      <td>1310.24</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.63</td>\n",
       "      <td>171.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01.01.2009 00:40:00</td>\n",
       "      <td>996.51</td>\n",
       "      <td>-8.31</td>\n",
       "      <td>265.12</td>\n",
       "      <td>-9.07</td>\n",
       "      <td>94.2</td>\n",
       "      <td>3.26</td>\n",
       "      <td>3.07</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.92</td>\n",
       "      <td>3.08</td>\n",
       "      <td>1309.19</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.50</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01.01.2009 00:50:00</td>\n",
       "      <td>996.51</td>\n",
       "      <td>-8.27</td>\n",
       "      <td>265.15</td>\n",
       "      <td>-9.04</td>\n",
       "      <td>94.1</td>\n",
       "      <td>3.27</td>\n",
       "      <td>3.08</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.92</td>\n",
       "      <td>3.09</td>\n",
       "      <td>1309.00</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.63</td>\n",
       "      <td>214.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Date Time  p (mbar)  T (degC)  Tpot (K)  Tdew (degC)  rh (%)  \\\n",
       "0  01.01.2009 00:10:00    996.52     -8.02    265.40        -8.90    93.3   \n",
       "1  01.01.2009 00:20:00    996.57     -8.41    265.01        -9.28    93.4   \n",
       "2  01.01.2009 00:30:00    996.53     -8.51    264.91        -9.31    93.9   \n",
       "3  01.01.2009 00:40:00    996.51     -8.31    265.12        -9.07    94.2   \n",
       "4  01.01.2009 00:50:00    996.51     -8.27    265.15        -9.04    94.1   \n",
       "\n",
       "   VPmax (mbar)  VPact (mbar)  VPdef (mbar)  sh (g/kg)  H2OC (mmol/mol)  \\\n",
       "0          3.33          3.11          0.22       1.94             3.12   \n",
       "1          3.23          3.02          0.21       1.89             3.03   \n",
       "2          3.21          3.01          0.20       1.88             3.02   \n",
       "3          3.26          3.07          0.19       1.92             3.08   \n",
       "4          3.27          3.08          0.19       1.92             3.09   \n",
       "\n",
       "   rho (g/m**3)  wv (m/s)  max. wv (m/s)  wd (deg)  \n",
       "0       1307.75      1.03           1.75     152.3  \n",
       "1       1309.80      0.72           1.50     136.1  \n",
       "2       1310.24      0.19           0.63     171.6  \n",
       "3       1309.19      0.34           0.50     198.0  \n",
       "4       1309.00      0.32           0.63     214.3  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mpl.rcParams['figure.figsize'] = (8, 6)\n",
    "mpl.rcParams['figure.dpi'] = 150\n",
    "mpl.rcParams['axes.grid'] = False\n",
    "\n",
    "df = pd.read_csv('/storage/data/tutorial/lstm/jena_climate_2009_2016.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d49ec5d5-4e5e-4ad5-b3c4-0ed43fa47746",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def univariate_data(dataset, start_index, end_index, history_size, target_size):\n",
    "    data = []\n",
    "    labels = []\n",
    "\n",
    "    start_index = start_index + history_size\n",
    "    if end_index is None:\n",
    "        end_index = len(dataset) - target_size\n",
    "\n",
    "    for i in range(start_index, end_index):\n",
    "        indices = range(i-history_size, i)\n",
    "        # Reshape data from (history`1_size,) to (history_size, 1)\n",
    "        data.append(np.reshape(dataset[indices], (history_size, 1)))\n",
    "        labels.append(dataset[i+target_size])\n",
    "    return np.array(data), np.array(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "183d39df-f3b8-4ee1-8cbb-7a5f9bf9f8b0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "range(-20, 0)\n",
      "range(-19, 1)\n",
      "range(-18, 2)\n",
      "range(-17, 3)\n",
      "range(-16, 4)\n",
      "range(-15, 5)\n",
      "range(-14, 6)\n",
      "range(-13, 7)\n",
      "range(-12, 8)\n",
      "range(-11, 9)\n"
     ]
    }
   ],
   "source": [
    "for i in range(0,10):\n",
    "    indices = range(i-20, i)\n",
    "    print(indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "56a0fea3-ad16-4c5a-a63f-84f0707591b9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date Time\n",
       "01.01.2009 00:10:00   -8.02\n",
       "01.01.2009 00:20:00   -8.41\n",
       "01.01.2009 00:30:00   -8.51\n",
       "01.01.2009 00:40:00   -8.31\n",
       "01.01.2009 00:50:00   -8.27\n",
       "Name: T (degC), dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uni_data = df['T (degC)']\n",
    "uni_data.index = df['Date Time']\n",
    "uni_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2f49de40-68a6-454c-ae2b-7939f54c0e67",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<Axes: xlabel='Date Time'>], dtype=object)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "uni_data.plot(subplots=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ab44e59a-3573-4a47-9218-d7ef1eaa0588",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#将数据集转换为数组类型\n",
    "uni_data = uni_data.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e8187faf-4ddd-4f96-9879-c190dfb8c867",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#标准化\n",
    "uni_train_mean = uni_data[:TRAIN_SPLIT].mean()\n",
    "uni_train_std = uni_data[:TRAIN_SPLIT].std()\n",
    "\n",
    "uni_data = (uni_data-uni_train_mean)/uni_train_std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5c91da18-5cd8-4bbf-99ea-fd734ea67e04",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#写函数来划分特征和标签\n",
    "univariate_past_history = 20\n",
    "univariate_future_target = 0\n",
    "x_train_uni, y_train_uni = univariate_data(uni_data, 0, TRAIN_SPLIT, # 起止区间\n",
    "                                           univariate_past_history,\n",
    "                                           univariate_future_target)\n",
    "x_val_uni, y_val_uni = univariate_data(uni_data, TRAIN_SPLIT, None,\n",
    "                                       univariate_past_history,\n",
    "                                       univariate_future_target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2fa2e8d8-f936-41fe-b4aa-a72032e8f6d2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(299980, 20, 1)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train_uni.shape"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
